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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Tools, model specs and courses for LLM engineers-VRAM calculator, benchmarks and model directory-with free and paid tiers.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Browser-based AI dev workspace by Google for full-stack apps; being sunset on 22 Mar 2027, no new workspaces.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦VRAM/GPU-memory calculator for LLMs
- ✦LLM performance rankings and benchmarks
- ✦Model directory and comparison
- ✦AI/ML courses and learning roadmap
- ✦Calculator API and exportable cost reports
- ✦Engineering blog and guides
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦Cloud workspaces for full-stack development
- ✦App Prototyping agent from natural language
- ✦Gemini AI for coding, debugging and docs
- ✦Repo import from GitHub, GitLab and Bitbucket
- ✦Web previews and Android emulators
- ✦Deploy to Firebase App Hosting, Hosting or Cloud Run
- ✦Design canvas integrated directly into the IDE (VSCode/Cursor)
- ✦Agent-driven MCP canvas based on open design format
- ✦AI Multiplayer for generating screens and flows in parallel
- ✦Design as Code: Design files live in repo, versioned with Git
- ✦Pixel-perfect vector-to-code workflow
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Estimating GPU memory before training or inference
- →Comparing and selecting LLMs
- →Learning ML and LLM engineering
- →Modeling production deployment costs
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Prototyping apps from a prompt or mockup
- →Building full-stack apps in the browser
- →Collaborating and sharing preview URLs
- →Deploying and monitoring apps quickly
- →Designing new products and features with pixel-perfect precision without leaving the development environment.
- →Eliminating design handoffs by having design and code live under one roof.
- →Accelerating workflow by using AI multiplayer to generate UI components and flows.
- →Shipping production-ready apps with guaranteed code-design alignment.
- →Integrating existing design systems directly from the codebase.